{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt \n",
    "from matplotlib.pyplot import figure\n",
    "import matplotlib.cm as cm\n",
    "from matplotlib import font_manager as fm\n",
    "import numpy as np\n",
    "from datetime import timedelta\n",
    "from IPython.display import display\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Settings to use for all plots\n",
    "figsize = (12,8)\n",
    "size = 300\n",
    "secs = 3600\n",
    "beams = [\"Low\", \"Medium\", \"High\"]\n",
    "\n",
    "# Fonts to be used in plots\n",
    "tfont = fm.FontProperties(family='STIXGeneral', weight='bold', size=30)\n",
    "lfont = fm.FontProperties(family='STIXGeneral', math_fontfamily=\"stix\", size=25, weight=\"bold\")\n",
    "tick_font = fm.FontProperties(family='STIXGeneral', math_fontfamily=\"stix\", size=20)\n",
    "bar_font = fm.FontProperties(family='STIXGeneral', math_fontfamily=\"stix\", size=25)\n",
    "legend_font = fm.FontProperties(family='STIXGeneral', math_fontfamily=\"stix\", size=30)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_files = []\n",
    "\n",
    "for root, dirs, files in sorted(os.walk(\"./icpp_training_results\")):\n",
    "    if \"early_termination\" in root:\n",
    "        for i in files:\n",
    "            f = os.path.join(root, i)\n",
    "            data_files.append(f)\n",
    "\n",
    "data_files = sorted(data_files)\n",
    "all_stopping = [pd.read_csv(data_files[0]), pd.read_csv(data_files[-3]), pd.read_csv(data_files[1]), pd.read_csv(data_files[-2]), pd.read_csv(data_files[2]), pd.read_csv(data_files[-1])]"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Figure 2 - Predicted Model Accuracy vs. Observed Accuracy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_epoch_converged(arch_df):\n",
    "    sorted_by_epoch = arch_df.sort_values('epoch')\n",
    "    try:\n",
    "        converged = sorted_by_epoch[sorted_by_epoch.converged==True].iloc[0]\n",
    "        return pd.Series({'epoch_converged': converged['epoch'], 'final_fitness': sorted_by_epoch['val_accs'].iloc[-1], 'prediction':converged['predictions']})\n",
    "    except:\n",
    "        return pd.Series({'epoch_converged': np.inf, 'final_fitness': sorted_by_epoch['val_accs'].iloc[-1], 'prediction':None})\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 GPU - 1e15 - No A4NN\n",
      "    arch  epoch_converged  final_fitness  prediction\n",
      "9      9              9.0      99.987402   97.726776\n",
      "33    33              9.0      99.981104   96.749503\n",
      "82    82              9.0      98.904006   89.177712\n",
      "98    98              9.0      97.442681   89.334014\n",
      "61    61              9.0      99.483497   94.791125\n",
      "55    55             10.0      99.930713   97.606809\n",
      "58    58             10.0      97.952885   92.716285\n",
      "6      6             10.0      99.911817   99.324454\n",
      "37    37             10.0      99.533888   95.852044\n",
      "38    38             11.0      99.943311   99.614529\n",
      "7      7             11.0      97.864701   93.434028\n",
      "83    83             11.0      99.943311   98.963262\n",
      "64    64             11.0      98.929201   88.219842\n",
      "54    54             11.0      99.111867   92.787099\n",
      "91    91             11.0      99.905518   98.770422\n",
      "51    51             11.0      98.563870   93.837877\n",
      "88    88             11.0      98.664651   91.570552\n",
      "2      2             11.0      99.918115   98.678220\n",
      "73    73             12.0      99.993701   99.470813\n",
      "62    62             12.0      99.086672   93.500311\n",
      "Percent Converged is:  73.0\n",
      "Avg epoch converged (for those converged) is:  11.945205479452055\n",
      "converged arches and their earliest convergence:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>arch</th>\n",
       "      <th>epoch_converged</th>\n",
       "      <th>final_fitness</th>\n",
       "      <th>prediction</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>99.281935</td>\n",
       "      <td>99.788292</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>16.0</td>\n",
       "      <td>99.559083</td>\n",
       "      <td>94.197689</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>11.0</td>\n",
       "      <td>99.918115</td>\n",
       "      <td>98.678220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>10.0</td>\n",
       "      <td>99.911817</td>\n",
       "      <td>99.324454</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>7</td>\n",
       "      <td>11.0</td>\n",
       "      <td>97.864701</td>\n",
       "      <td>93.434028</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   arch  epoch_converged  final_fitness  prediction\n",
       "0     0             24.0      99.281935   99.788292\n",
       "1     1             16.0      99.559083   94.197689\n",
       "2     2             11.0      99.918115   98.678220\n",
       "6     6             10.0      99.911817   99.324454\n",
       "7     7             11.0      97.864701   93.434028"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 1 GPU - 1e15 - No A4NN\n",
    "df = pd.read_csv(data_files[4])\n",
    "\n",
    "by_arch = df.groupby('arch')\n",
    "where_converged = by_arch.apply(get_epoch_converged).reset_index()  \n",
    "\n",
    "print(\"1 GPU - 1e15 - No A4NN\")\n",
    "print(where_converged.sort_values('epoch_converged', ascending=True).iloc[20:40])\n",
    "\n",
    "percent_converged = len(where_converged[where_converged.epoch_converged!=np.inf].index) / len(where_converged.index) * 100\n",
    "print(\"Percent Converged is: \", percent_converged)\n",
    "\n",
    "mean = where_converged[where_converged.epoch_converged!=np.inf].epoch_converged.mean()\n",
    "print(\"Avg epoch converged (for those converged) is: \", mean)\n",
    "\n",
    "print(\"converged arches and their earliest convergence:\")\n",
    "only_converged_arches = pd.DataFrame(where_converged.loc[where_converged.epoch_converged!=np.inf,:])\n",
    "only_converged_arches.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
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",
      "text/plain": [
       "<Figure size 2400x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "arch_44 = df[df['arch']==38]\n",
    "fig, ax = plt.subplots(layout='constrained', figsize=(12,5), dpi=200)\n",
    "\n",
    "a, b, c = 100.2, 1.15, 17\n",
    "\n",
    "x = np.linspace(0.5,26,200)\n",
    "y = a-b**(c-x)\n",
    "\n",
    "epochs, fitness = arch_44['epoch'].to_list(), arch_44['val_accs'].to_list()\n",
    "prediction, actual = 99.614529, 99.943311\n",
    "\n",
    "ax.plot(x,y,color=\"#2C4D96\", label=\"Fitted Parametric Function\", linewidth=3)\n",
    "\n",
    "ax.scatter(epochs, fitness,  marker='o', edgecolors='black', facecolor=\"none\",linewidths=2, s= 100, label='Observed Accuracy', zorder=3)\n",
    "ax.vlines(12,90,101,colors='#990000',linestyles=\":\",linewidth=4, label=\"Prediction Converged\", zorder=3)\n",
    "ax.axvspan(12, 26, color = 'k', alpha = 0.2, label=\"Avoidable Training\")\n",
    "\n",
    "text_font = fm.FontProperties(family='STIXGeneral', math_fontfamily=\"stix\", size=25)\n",
    "ax.annotate('Predicted Accuracy = {:.2f}'.format(prediction), xy=(0.63, 0.65), xycoords='axes fraction', font=text_font, zorder=3)\n",
    "ax.annotate('Actual accuracy = {:.2f}'.format(actual), xy=(0.63, 0.74), xycoords='axes fraction', font=text_font, zorder=3)\n",
    "\n",
    "ax.set_ylim(90, 101)\n",
    "ax.set_xlim(0, 25)\n",
    "ax.grid(zorder=-1)\n",
    "ax.set_ylabel(\"Accuracy (%)\", font=lfont)\n",
    "ax.set_xlabel(\"Number of Epochs\", font=lfont)\n",
    "xticks_labels = ['0', '5', '10', '15', '20', '25']\n",
    "ax.set_xticklabels(xticks_labels, color= \"black\" , font=tick_font)\n",
    "ax.set_yticklabels(ax.get_yticks(), color= \"black\" , font=tick_font)\n",
    "ax.legend(loc='lower right', prop=tick_font)\n",
    "\n",
    "plt.savefig('figures/figure2.png', bbox_inches='tight')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "## Figure 5 - Single GPU Pareto Optimal Architectures "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def one_line_per_arch_a4nn(arch_df):\n",
    "    sorted_by_epoch = arch_df.sort_values('epoch', ascending=False)\n",
    "    if sorted_by_epoch['converged'].iloc[0] == True:\n",
    "        to_return = sorted_by_epoch['predictions'].iloc[0]\n",
    "    else:\n",
    "        to_return = sorted_by_epoch['val_accs'].iloc[0]\n",
    "    return pd.Series({'final_acc':to_return, 'flops':arch_df['flops'].iloc[0], 'converged':sorted_by_epoch['converged'].iloc[0]})\n",
    "\n",
    "def one_line_per_arch(arch_df):\n",
    "    sorted_by_epoch = arch_df.sort_values('epoch', ascending=False)\n",
    "    to_return = sorted_by_epoch['val_accs'].iloc[0]\n",
    "    return pd.Series({'final_acc':to_return, 'flops':arch_df['flops'].iloc[0], 'converged':sorted_by_epoch['converged'].iloc[0]})\n",
    "\n",
    "def is_pareto_efficient_simple(unadjusted_costs):\n",
    "    \"\"\"\n",
    "    Find the pareto-efficient points\n",
    "    :param costs: An (n_points, n_costs) array\n",
    "    :return: A (n_points, ) boolean array, indicating whether each point is Pareto efficient\n",
    "    \"\"\"\n",
    "\n",
    "    # this assumes minimization\n",
    "    costs = np.zeros(unadjusted_costs.shape, dtype=float)\n",
    "    costs[:,1] = unadjusted_costs[:,1]\n",
    "    costs[:,0] = unadjusted_costs[:,0] * -1\n",
    "    \n",
    "    is_efficient = np.ones(costs.shape[0], dtype = bool)\n",
    "    for i, c in enumerate(costs):\n",
    "        if is_efficient[i]:\n",
    "            is_efficient[is_efficient] = np.any(costs[is_efficient]<c, axis=1)  # Keep any point with a lower cost\n",
    "            is_efficient[i] = True \n",
    "    return is_efficient"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<bound method NDFrame.head of     arch  final_acc     flops  converged\n",
      "0      0  94.601915  740.0186      False\n",
      "1      1  80.436958  893.3620       True\n",
      "2      2  98.059965  993.3537      False\n",
      "3      3  97.466093  731.0186       True\n",
      "4      4  97.922044  917.7927       True\n",
      "..   ...        ...       ...        ...\n",
      "95    95  93.058705  615.0427      False\n",
      "96    96  85.127449  715.4103       True\n",
      "97    97  98.154447  860.0849      False\n",
      "98    98  95.838047  713.0186       True\n",
      "99    99  99.532435  661.6971       True\n",
      "\n",
      "[100 rows x 4 columns]>\n",
      "<bound method NDFrame.head of     arch  final_acc      flops  converged\n",
      "0      0  92.622012   740.0186       True\n",
      "1      1  99.414210   893.3620      False\n",
      "2      2  97.846239   993.3537       True\n",
      "3      3  96.689185   731.0186       True\n",
      "4      4  99.930713   917.7927      False\n",
      "..   ...        ...        ...        ...\n",
      "95    95  96.009714   535.0669       True\n",
      "96    96  96.439102   635.1375       True\n",
      "97    97  99.836231   795.6629      False\n",
      "98    98  98.240206  1100.1861       True\n",
      "99    99  60.969987     0.0161       True\n",
      "\n",
      "[100 rows x 4 columns]>\n",
      "<bound method NDFrame.head of     arch   final_acc     flops  converged\n",
      "0      0   97.613070  740.0186       True\n",
      "1      1   95.940147  893.3620       True\n",
      "2      2   99.255902  993.3537       True\n",
      "3      3   97.802500  731.0186       True\n",
      "4      4  100.000000  917.7927      False\n",
      "..   ...         ...       ...        ...\n",
      "95    95   96.458188  726.5493       True\n",
      "96    96   99.937012  640.0370      False\n",
      "97    97  100.000000  615.0427      False\n",
      "98    98  100.000000  830.8225      False\n",
      "99    99   99.890475  650.7559       True\n",
      "\n",
      "[100 rows x 4 columns]>\n",
      "<bound method NDFrame.head of     arch  final_acc     flops  converged\n",
      "0      0  94.053918  740.0186       True\n",
      "1      1  95.616024  893.3620      False\n",
      "2      2  97.996977  993.3537       True\n",
      "3      3  94.375157  731.0186       True\n",
      "4      4  98.015873  917.7927      False\n",
      "..   ...        ...       ...        ...\n",
      "95    95  97.707231  695.5480       True\n",
      "96    96  98.293021  712.9844      False\n",
      "97    97  98.293021  677.2712      False\n",
      "98    98  97.763920  597.5721       True\n",
      "99    99  92.233560  450.7927       True\n",
      "\n",
      "[100 rows x 4 columns]>\n",
      "<bound method NDFrame.head of     arch  final_acc     flops  converged\n",
      "0      0  99.281935  740.0186       True\n",
      "1      1  99.559083  893.3620       True\n",
      "2      2  99.918115  993.3537       True\n",
      "3      3  99.685059  731.0186      False\n",
      "4      4  99.905518  917.7927      False\n",
      "..   ...        ...       ...        ...\n",
      "95    95  99.074074  740.0186      False\n",
      "96    96  98.412698  597.3296       True\n",
      "97    97  99.981104  904.2344       True\n",
      "98    98  97.442681  624.0427       True\n",
      "99    99  99.937012  695.2712       True\n",
      "\n",
      "[100 rows x 4 columns]>\n",
      "<bound method NDFrame.head of     arch   final_acc     flops  converged\n",
      "0      0  100.000000  740.0186      False\n",
      "1      1  100.000000  893.3620      False\n",
      "2      2  100.000000  993.3537      False\n",
      "3      3  100.000000  731.0186       True\n",
      "4      4  100.000000  917.7927      False\n",
      "..   ...         ...       ...        ...\n",
      "95    95   99.981104  613.4673      False\n",
      "96    96   97.927690  251.2500       True\n",
      "97    97  100.000000  514.9177      False\n",
      "98    98   99.754346  352.8169       True\n",
      "99    99  100.000000  759.3962      False\n",
      "\n",
      "[100 rows x 4 columns]>\n",
      "<bound method NDFrame.head of     arch  final_acc      flops  converged\n",
      "0      0  96.172087   740.0186       True\n",
      "1      1  95.792391   893.3620      False\n",
      "2      2  99.227193   993.3537       True\n",
      "3      3  94.885362   731.0186      False\n",
      "4      4  99.517733   917.7927       True\n",
      "..   ...        ...        ...        ...\n",
      "95    95  99.839760  1109.0427       True\n",
      "96    96  92.929161   434.6550       True\n",
      "97    97  97.108844   973.0611      False\n",
      "98    98  96.850592   704.1177      False\n",
      "99    99  99.383542   679.4103       True\n",
      "\n",
      "[100 rows x 4 columns]>\n",
      "<bound method NDFrame.head of     arch  final_acc      flops  converged\n",
      "0      0  95.610953   740.0186       True\n",
      "1      1  99.539680   893.3620       True\n",
      "2      2  98.084373   993.3537       True\n",
      "3      3  90.386256   731.0186       True\n",
      "4      4  99.271240   917.7927       True\n",
      "..   ...        ...        ...        ...\n",
      "95    95  99.378492   893.3721       True\n",
      "96    96  99.899219   893.3721      False\n",
      "97    97  97.822203   708.8362       True\n",
      "98    98  99.955908  1064.7598      False\n",
      "99    99  97.516150   904.5112       True\n",
      "\n",
      "[100 rows x 4 columns]>\n",
      "<bound method NDFrame.head of     arch   final_acc     flops  converged\n",
      "0      0   97.502926  740.0186       True\n",
      "1      1  100.000000  893.3620      False\n",
      "2      2  100.000000  993.3537      False\n",
      "3      3   97.788697  731.0186       True\n",
      "4      4   98.243795  917.7927       True\n",
      "..   ...         ...       ...        ...\n",
      "95    95   97.446638  515.2046       True\n",
      "96    96   99.155418  679.6971       True\n",
      "97    97   99.771448  613.1805       True\n",
      "98    98   97.688875  526.0669       True\n",
      "99    99  100.000000  679.6971      False\n",
      "\n",
      "[100 rows x 4 columns]>\n"
     ]
    }
   ],
   "source": [
    "all_paretos = pd.DataFrame()\n",
    "for i in data_files:  \n",
    "    df = pd.read_csv(i)\n",
    "    by_arch = df.groupby('arch')\n",
    "\n",
    "    if \"1e14\" in i:\n",
    "        beam = \"Low\"\n",
    "    elif \"1e15\" in i:\n",
    "        beam = \"Medium\"\n",
    "    elif \"1e16\" in i:  \n",
    "        beam = \"High\"    \n",
    "\n",
    "    if \"no_early_termination\" in i:  \n",
    "        stop = False\n",
    "        one_line = by_arch.apply(one_line_per_arch).sort_values('arch', ascending=True).reset_index()  \n",
    "    else: \n",
    "        stop = True  \n",
    "        one_line = by_arch.apply(one_line_per_arch_a4nn).sort_values('arch', ascending=True).reset_index()\n",
    "\n",
    "    if \"1gpu\" in i:  \n",
    "        gpu = 1  \n",
    "    elif \"4gpu\" in i:  \n",
    "        gpu = 4  \n",
    "\n",
    "    print(one_line.head)\n",
    "    sorted_by_fitness = one_line.sort_values('final_acc', ascending=False).head()\n",
    "    costs = one_line[['final_acc', 'flops']].to_numpy()\n",
    "    pareto_optimals = is_pareto_efficient_simple(costs) \n",
    "    one_line['pareto_optimal'] = pareto_optimals\n",
    "    pareto_optimal_arches = one_line.loc[one_line['pareto_optimal'] == True].copy()\n",
    "\n",
    "    pareto_optimal_arches['beam'] = beam\n",
    "    pareto_optimal_arches['gpus'] = gpu\n",
    "    pareto_optimal_arches['stop'] = stop\n",
    "\n",
    "    all_paretos = pd.concat([all_paretos, pareto_optimal_arches], ignore_index=True)\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Figure 5a - 1 GPU With A4NN Workflow"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(-55.894965000000006, 1173.794265)\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 1920x1280 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 1 GPU - with A4NN\n",
    "df = all_paretos.copy()\n",
    "fig, ax = plt.subplots(layout='constrained', figsize=figsize, dpi=160)\n",
    "\n",
    "plt.xlabel('FLOPS', color='black', font=lfont)\n",
    "plt.ylabel('Validation Accuracy', color='black', font=lfont)\n",
    "plt.ylim(90, 100.2)\n",
    "\n",
    "markers = [\"o\", \"^\"]\n",
    "size=400\n",
    "\n",
    "low, medium, high = (df['beam'] == \"Low\"), (df['beam'] == \"Medium\"), (df['beam'] == \"High\")\n",
    "gpu1, gpu4 = (df['gpus'] == 1), (df['gpus'] == 4)\n",
    "no_stop, stop = (df['stop'] == False), (df['stop'] == True)\n",
    "\n",
    "low_peng_acc = df.loc[low & gpu1 & stop]['final_acc'].to_numpy()\n",
    "low_peng_flops = df.loc[low & gpu1 & stop]['flops'].to_numpy()\n",
    "\n",
    "med_peng_acc = df.loc[medium & gpu1 & stop]['final_acc'].to_numpy()\n",
    "med_peng_flops = df.loc[medium & gpu1 & stop]['flops'].to_numpy()\n",
    "\n",
    "high_peng_acc = df.loc[high & gpu1 & stop]['final_acc'].to_numpy()\n",
    "high_peng_flops = df.loc[high & gpu1 & stop]['flops'].to_numpy()\n",
    "\n",
    "colors = cm.viridis(np.linspace(0.2, 0.95, 3))\n",
    "l2 = ax.scatter(low_peng_flops, low_peng_acc,  s=size, marker= \"o\" , color=colors[0], zorder=3)\n",
    "l4 = ax.scatter(med_peng_flops, med_peng_acc, s=size, marker= \"^\" , color=colors[1], zorder=3)\n",
    "l6 = ax.scatter(high_peng_flops, high_peng_acc, s=size, marker= \"*\" , color=\"xkcd:orange\", zorder=3)\n",
    "l7 = ax.scatter([0], [0], s=size, marker='o', color= colors[0] , label= \"Low Beam\" )\n",
    "l8 = ax.scatter([0], [0], s=size, marker='^', color= colors[1] , label= \"Medium Beam\" )\n",
    "l9 = ax.scatter([0], [0], s=size, marker=\"*\", color= \"xkcd:orange\", label=\"High Beam\")\n",
    "ax.grid(zorder=-1)\n",
    "\n",
    "print(ax.get_xlim())\n",
    "\n",
    "ax.set_xticklabels(ax.get_xticks(), color= \"black\" , font=tick_font)\n",
    "ax.set_yticklabels(ax.get_yticks(), color= \"black\" , font=tick_font)\n",
    "ax.legend(handles=[l7, l8, l9], loc= \"lower right\" , prop=legend_font)\n",
    "\n",
    "ax.set_xticklabels(ax.get_xticks(), color= \"black\" , font=tick_font)\n",
    "ax.set_yticklabels(ax.get_yticks(), color= \"black\" , font=tick_font)\n",
    "plt.savefig('figures/figure5a.png')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Figure 5b -1 GPU with NSGA-Net Only"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1920x1280 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 1 GPU - without A4NN\n",
    "fig, ax = plt.subplots(layout='constrained', figsize=figsize, dpi=160)\n",
    "\n",
    "plt.xlabel('FLOPS', color='black', font=lfont)\n",
    "plt.ylabel('Validation Accuracy', color='black', font=lfont)\n",
    "plt.ylim(90, 100.2)\n",
    "\n",
    "markers = [\"o\", \"^\"]\n",
    "\n",
    "low, medium, high = (df['beam'] == \"Low\"), (df['beam'] == \"Medium\"), (df['beam'] == \"High\")\n",
    "gpu1, gpu4 = (df['gpus'] == 1), (df['gpus'] == 4)\n",
    "no_stop, stop = (df['stop'] == False), (df['stop'] == True)\n",
    "\n",
    "low_acc = df.loc[low & gpu1 & no_stop]['final_acc'].to_numpy()\n",
    "low_flops = df.loc[low & gpu1 & no_stop]['flops'].to_numpy()\n",
    "\n",
    "med_acc = df.loc[medium & gpu1 & no_stop]['final_acc'].to_numpy()\n",
    "med_flops = df.loc[medium & gpu1 & no_stop]['flops'].to_numpy()\n",
    "\n",
    "high_acc = df.loc[high & gpu1 & no_stop]['final_acc'].to_numpy()\n",
    "high_flops = df.loc[high & gpu1 & no_stop]['flops'].to_numpy()\n",
    "\n",
    "size=400\n",
    "colors = cm.viridis(np.linspace(0.2, 0.95, 3))\n",
    "cmap = cm.get_cmap('viridis', 3)\n",
    "\n",
    "l1 = ax.scatter(low_flops, low_acc, marker= \"o\" , s=size, color=colors[0], label= \"Low Beam\", zorder=3)\n",
    "l3 = ax.scatter(med_flops, med_acc, marker= \"^\" , s=size, color=colors[1], label= \"Medium Beam\", zorder=3)\n",
    "l5 = ax.scatter(high_flops, high_acc, s=size, marker= \"*\" , color=\"xkcd:orange\", label= \"High Beam\", zorder=3)\n",
    "l7 = ax.scatter([0], [0], s=size, marker='o', color= colors[0] , label= \"Low Beam\" )\n",
    "l8 = ax.scatter([0], [0], s=size, marker='^', color= colors[1] , label= \"Medium Beam\" )\n",
    "l9 = ax.scatter([0], [0], s=size, marker=\"*\", color= \"xkcd:orange\", label=\"High Beam\")\n",
    "\n",
    "ax.grid(zorder=-1)\n",
    "ax.set_xlim((-55.89, 1173))\n",
    "ax.set_xticklabels(ax.get_xticks(), color= \"black\" , font=tick_font)\n",
    "ax.set_yticklabels(ax.get_yticks(), color= \"black\" , font=tick_font)\n",
    "ax.legend(handles=[l7, l8, l9], loc= \"lower right\" , prop=legend_font)\n",
    "\n",
    "ax.set_xticklabels(ax.get_xticks(), color= \"black\" , font=tick_font)\n",
    "ax.set_yticklabels(ax.get_yticks(), color= \"black\" , font=tick_font)\n",
    "plt.savefig('figures/figure5b.png')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Figure 6 - Epoch Savings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Avg. epochs completed for Low: 2134.0\n",
      "Avg. percent epochs saved for Low: 14.639999999999997\n",
      "\n",
      "Avg. epochs completed for Medium: 1573.0\n",
      "Avg. percent epochs saved for Medium: 37.08\n",
      "\n",
      "Avg. epochs completed for High: 1688.0\n",
      "Avg. percent epochs saved for High: 32.48\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1400x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_epochs_savings(beams, num_epochs_no_stop, stop_1e14, stop_1e15, stop_1e16):\n",
    "    epochs_run = {\n",
    "        'NSGA-Net': np.repeat(num_epochs_no_stop, 3),\n",
    "        'A4NN (1 GPU)': (stop_1e14[0], stop_1e15[0], stop_1e16[0]),\n",
    "        'A4NN (4 GPUs)': (stop_1e14[1], stop_1e15[1], stop_1e16[1]),\n",
    "    }\n",
    "\n",
    "    x = np.arange(len(beams))  # the label locations\n",
    "    width = 0.25  # the width of the bars\n",
    "    multiplier = 0\n",
    "\n",
    "    fig, ax = plt.subplots(layout='constrained', figsize=(14, 8))\n",
    "    colors = [\"xkcd:grey\", \"xkcd:orange\", \"xkcd:blue\"]\n",
    "    bar_font = fm.FontProperties(family='STIXGeneral', math_fontfamily=\"stix\", size=25)\n",
    "    for index, (label, num_epochs) in enumerate(epochs_run.items()):\n",
    "        offset = width * multiplier\n",
    "        rects = ax.barh(x + offset, num_epochs, width, label=label, color=colors[index]) \n",
    "    \n",
    "        labels = [str(round((1-(num_epochs[i]/num_epochs_no_stop))*100, 1))+'%' for i in range(len(num_epochs))]\n",
    "        if any(float(i.split('%')[0].strip()) > 0.0  for i in labels):\n",
    "            ax.bar_label(rects, labels=labels, padding=2, font=bar_font)\n",
    "        multiplier += 1\n",
    "\n",
    "    # Add some text for labels, title and custom x-axis tick labels, etc.\n",
    "    ax.set_xlabel('Number of Epochs', font=lfont)\n",
    "    ax.xaxis.label.set_color('black')\n",
    "    ax.set_ylabel('Beam Intensity', font=lfont)\n",
    "    ax.yaxis.label.set_color('black')\n",
    "    ax.set_xlim(0, 2700)\n",
    "\n",
    "    ax.set_yticks(x + width, beams)\n",
    "    xticks = [int(x) for x in ax.get_xticks()]\n",
    "    ax.set_xticklabels(xticks, color='black', font=tick_font)\n",
    "    ax.set_yticklabels(beams, color='black', font=tick_font)\n",
    "\n",
    "    handles, labels = plt.gca().get_legend_handles_labels()\n",
    "    order = [0, 1, 2]\n",
    "\n",
    "    ax.legend([handles[idx] for idx in order],[labels[idx] for idx in order], loc=\"upper center\", bbox_to_anchor=(0.5, -0.1),  ncol=3, prop=legend_font, frameon=False)\n",
    "\n",
    "    plt.savefig('figures/figure6.png')\n",
    "    display(fig)\n",
    "    plt.close()\n",
    "    return\n",
    "\n",
    "def calculate_and_plot_epochs_savings(files):\n",
    "    no_stop_1e14, no_stop_1e15, no_stop_1e16 = [], [], []\n",
    "    stop_1e14, stop_1e15, stop_1e16 = [], [], []\n",
    "    stop_1e14_len, stop_1e15_len, stop_1e16_len = [], [], []\n",
    "   \n",
    "    for f in files: \n",
    "        if \"no\" in f:\n",
    "            df = pd.read_csv(f)\n",
    "            num_epochs_no_stopping = len(df.index) # non-stopped file\n",
    "\n",
    "            if \"1e14\" in f:\n",
    "                no_stop_1e14.append(df) \n",
    "            elif \"1e15\" in f:\n",
    "                no_stop_1e15.append(df)\n",
    "            elif \"1e16\" in f:\n",
    "                no_stop_1e16.append(df)\n",
    "\n",
    "        beam = f.split('/')[-1].split('_')[1].strip()\n",
    "        gpus = f.split('/')[-1].split('_')[0].strip()\n",
    "        stop = f.split('/')[-1].strip()\n",
    "        if \"termination\" in stop and not \"no\" in stop:\n",
    "            df = pd.read_csv(f)\n",
    "\n",
    "            if \"1e14\" in stop:\n",
    "                stop_1e14.append(df) \n",
    "                stop_1e14_len.append(len(df.index))\n",
    "            elif \"1e15\" in stop:\n",
    "                stop_1e15.append(df) \n",
    "                stop_1e15_len.append(len(df.index))\n",
    "            elif \"1e16\" in stop:\n",
    "                stop_1e16.append(df) \n",
    "                stop_1e16_len.append(len(df.index))\n",
    "\n",
    "    print()\n",
    "    avg_epochs_completed = [sum(stop_1e14_len)/len(stop_1e14_len), sum(stop_1e15_len)/len(stop_1e15_len), sum(stop_1e16_len)/len(stop_1e16_len)]\n",
    "    for i, b in enumerate(beams):\n",
    "        print(f\"Avg. epochs completed for {b}: {avg_epochs_completed[i]}\")\n",
    "        percent_epochs_saved = 1-(avg_epochs_completed[i]/num_epochs_no_stopping)\n",
    "        print(f\"Avg. percent epochs saved for {b}: {percent_epochs_saved*100}\\n\")\n",
    "\n",
    "    plot_epochs_savings(beams, num_epochs_no_stopping, stop_1e14_len, stop_1e15_len, stop_1e16_len)\n",
    "\n",
    "    return [no_stop_1e14, no_stop_1e15, no_stop_1e16], [stop_1e14, stop_1e15, stop_1e16]\n",
    "\n",
    "no_stop, stop = calculate_and_plot_epochs_savings(data_files)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Figure 7 - Violin Plot of Convergence"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "percent converged is: 61.0\n",
      "percent converged is: 67.0\n",
      "percent converged is: 69.0\n",
      "percent converged is: 80.0\n",
      "percent converged is: 56.00000000000001\n",
      "percent converged is: 57.99999999999999\n"
     ]
    },
    {
     "data": {
      "image/png": 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7du3aDOs7ceKETflq1aplGgMDEHiaxMREM3LkSCPJDB061C4Rl/oYNWqU3dRHN1+xXqZMGaePu2TJEpt9e/XqleXXQL8JT/XOO+/YtKM33njDZnvXrl1ttq9atSrTOi9cuGAzJUypUqWyFSPtE54os7bpLMacBR+JdTchsZ6/PPzwwzYfikuXLnVqv8GDB7u8X14k1uPj460/FpecnGxdf+7cOVOrVi3rsW/+wPzxxx+dSkoAeSkv22eqa9euWX+s7R//+EdWQ3eI9onCIjdOet18FV2VKlUcJriNMSYhIcH07dvXpnzXrl2z9ZoYgKCwiYyMNM2bNzeSzHPPPWddP2fOHFOyZEm75PoTTzxhs//169dttt9yyy1OH/uXX36x2XfQoEFZeg30m/Bk169fN1WrVrX+n9/8vbRjx4427ezAgQNO1du6dess7Xcz2ic8VWZt0xmMOQsHZ/O73gIKsWLFimVpv/r169ssHz16NCfCybY33nhDx44d0+TJk+Xj4yNJSklJ0cCBA7V//35J0uOPP64BAwbY7HfPPffoypUrOnHiRJ7HDKTHHe1z0aJFio6OliQNHDgwS8dPD+0ThUVycrLNctmyZTPdx9fXV927d7cup6SkaOPGjdbl1157TW3btrUuHz16VE2aNNH333+vS5cuKTY2Vnv27NFbb72l2rVra9++fTb1N2nSJKsvRwkJCfrnP/+p+vXra+TIkdb158+fV9u2bbVs2TJJ0nfffadXXnlFrVq10siRIzV9+nS9+OKLWT4ukFsuX76stm3bauPGjerTp4/effdd67b+/ftr9+7d6ty5s80+kyZN0pw5c6zLfn5+Cg8Pty7Hx8c7ffyEhASb5dKlS7v6EiTRb8Kz+fn56d5777UuX7582Wa7u8extE94qszapjMYc3oWEuso1NIOGCQpLi7Oqf0qVapks3zlypWcCinLDhw4oPfee0+DBw9W69atres//vhjrVmzRpIUEhKi8ePH2+3r5eWlKlWq6O+//86zeIHMuKN9zp49W9KNwUq3bt2c3i8ztE8UJrkxmPfz89OSJUv04IMPysvLS5J04sQJDRo0SOHh4SpWrJjq1aun8ePH67777tNjjz1mU1e7du2yFJPEAASFz0MPPaT9+/fLy8tLH3zwgd320qVLa/HixRo2bJjN+hdffFHGGOtyjRo1rM8TExOtSYDMnD9/3ma5Vq1aroQviX4TkGz7Nn9/f5tt7hzH0j7h6TJqm85gzOlZfN0dAJCbateubbN86dIlp/YLDg62Wc7Kh2lOe/zxxxUQEGBzVVJiYqLeeust6/KoUaNUvHhxh/unpKTIz88vt8MEnJbX7TMuLk4LFy6UJPXq1UtFihRxaj9n0D5RmOTWYD4wMFBfffWVRo8ere+//15btmzRxYsXFRwcrHLlyqlDhw7q37+/SpcubXO1bVhYmDp06JCl15JTA5CKFStm6fhATtu2bZvmz58vSWrRooWqVq3qsJyPj4+++OILnTx5UsuXL5ckHTp0SFu2bNEdd9whSapbt67++OMP6z5///23QkNDM43hzJkzNst169Z1+XXQbwJSRESE9fnNd364cxxL+4Sny6htZoYxp+chsY5C7eZbxw8fPuzUfqlXtKUKCwvLsZiyYtasWVqxYoXef/99lSlTxrp+1apVioyMtC4//PDD6dZx/vx5u2QJ4E553T7nz59vvdU9J2/Jo32isMntwXzDhg3VsGHDdOs5cOCAVqxYYV0ePHiwfH2z9pWVAQgKm8WLF1uf16lTJ8Oy3t7eevfdd9WoUSPrum3btlkT63feeac+//xz67ZDhw45dfX5oUOHrM9DQkJcnqqJfhO4IW3fdvO0a46+J3fq1CnTOrM7jqV9Ahm3zcww5vQ8TAWDQq18+fK6/fbbrcu7du1yar+rV6/aLKetI69FR0frmWeeUa1atfTkk0/abNuwYYP1eY0aNVStWjWHdZw/f17x8fFccYd8Ja/bZ+oteSEhITl2Sx7tE4WRu09Kv/vuu9bpKvz8/DR69Ogs1ZM6AHnllVcYgKDQOHnypPV5yZIlMy3fsGFD1atXz7qc9kRZx44dbdrttm3bnIrhzz//tD7v3LmzSyef6DeB/0k71ViXLl1strVo0UIlSpSwLmfle7KXl5dN+88M7RO4IaO2mRnGnJ6HxDoKvbQ/PLFmzRolJSVlus+RI0esz2+55Ra7eWPz0ksvvaRz585p0qRJdgOXtHNctm/fPt065s+fr3bt2lnntQXyi7xqn9HR0Vq6dKkkqXfv3goICMhCtPZonyiM3HlSevv27fr666+ty08//bTdFDPOYACCwirtLeWxsbFO7ZP2fzztVC/h4eHq2bOndXndunWZ1nXs2DGbqWAefPBBp2JIRb8J/E/qj2eXLVtWLVu2tNnm6+ur/v37W5dTp3TKTNrvyfXq1XPpJDftE7gho7aZEcacnonEOgq9kSNHWm9Pj4uL07x58zLdZ9OmTdbnw4YNs7sKL69s3bpVn376qe655x517NjRbnvaD+oKFSqkW8/nn3+e4RV5gLvkVfv8+eeflZiYKCnnbsmjfaIwc8dJ6eTkZA0bNkzJycmSbszb/Morr7hURyoGICis0k7/snPnTpf3v/mE16hRo6zPf//9d128eDHD/X/88Ufr86pVq9ok5jNDvwn8T3R0tGbOnClJev755x32Nf/617/k7X0jZZP6GwmZSfs9+dFHH3U6HtoncIMzbTM9jDk9E4l1FHolSpSwuY38vffes95i7kjas4wlSpTQs88+69RxLl++bLOckJDgerBpWCwWPfbYYypSpIg++OADh2XSDo7Su1X9hx9+kDFG3bt3z1Y8QG7Iq/aZekteaGioy7fzOUL7RGHnjpPSw4cP144dOyTdmOJi7ty5CgoKcqkOiQEICre+ffuqaNGikqT169fbTA3jSEpKijZv3ixJqlixot2Vd126dLH2QcnJyfrss8/Srev69euaOnWqdfntt9+2Jv0yQ7+Jwu7SpUsaN26cnnzySc2ePdt6kjg9Tz31lKKiotSpUyf985//dFimZs2aGjRokHX5nXfeybDOw4cPW6d0qlatmoYNG+ZU7LRPFGa50TbTw5jTQxnkqOjoaCPJREdHuzsUpBEfH2/q169vJBlJ5t1330237JgxY4wk4+PjY37++Wenj/HAAw9Y65dk7rvvvmzF/MknnxhJZvz48emWuXTpkilatKiRZJ599lm77ceOHTMRERHmzz//zFYsQG7K7fYZGRlpfH19jSTzwAMP5EjMtE94grFjx1rbZdOmTY3FYkm3bFRUlAkODjaSTIkSJczZs2ddOtbzzz9vPVZERITZuXNnlmJOSUkxd9xxhwkKCjInTpxwWGbatGnWY3322WcOy8yePds0btzYpKSkZCkOIDd99NFH1v/hnj17Zvh/OmnSJCPJeHl5mfnz5zssc/r0aRMWFmYkmZCQEHPs2DGH5d544w3rcV3tT+k3UdiNHDnSZixYq1Yts23bNodlX3nlFSPJtGrVysTExGRY74ULF8ytt95qrfeHH35It+zAgQONJBMUFGQ2bNjgdOy0TxRmudU2b8aYs/BxNr9LYj2HkVjPv86cOWPq1atnHVyMHTvWxMbGWrenpKSYiRMnGi8vLxMQEGC+//77DOtLSEgwO3bsMPPmzTODBw+2+bBOfQwfPtwsXLjQ7Nixw6UP5vPnz5vixYubqlWrmmvXrmVYdvLkyUaSKV68uDl06JB1/aZNm0zFihXNjBkznD4u4C453T7TmjJlirVNLliwINux0j7hKfLipHRCQoL5xz/+YT1G48aNzcmTJ7McMwMQeIqXX37ZeHl5GUmmR48edsnw69evmw8//ND4+voaPz8/M3Xq1Azr279/v6lSpYqRZKpXr25zcittHyzJDBkyxCQmJjodK/0mPMEzzzxjNxb09/c3Y8aMMQcOHDCXL182K1euNHfddZfx8fExTzzxRKbtIdXevXtN+fLljSTj5+dnJk2aZNMGExMTrf1wSEiIWbVqldNx0z5R2OVm20yLMWfhQ2LdTUis52/x8fFm7NixJjQ01EgyoaGhpkOHDqZXr16mfPnyxtfX1/Tq1cscPHgw07r+/PNPh8n09B4//fST03GmJuoXLlzoVPn333/fBAQEmODgYNOtWzdzxx13mPDwcDN37lynjwm4W062z7TatWtnrc+VREB6aJ/wJLl50mv58uWmdu3a1kTB//3f/2WrjTIAgadZvXq1adu2rZFkvL29TaNGjUzfvn3NXXfdZcLDw423t7fp1auX2b59u1P1RUZGmkceecQEBAQYb29v07RpU9OzZ09TsWJFI8nceuut5osvvnA5TvpNeILY2FgzZMgQ4+/vn+54sFixYuahhx7K0l1Zly9fNo8//rgJDAw0kkypUqVM586dTY8ePUzJkiVNkSJFzODBg83ff//tUr20TxR2ud02UzHmLHycze96GZPBZLZwWUxMjEJDQxUdHa2QkBB3h4N0XL9+XevXr9fevXsVHR2tYsWKqVy5cmrfvr1Lv5yeG65evaoPP/xQYWFhLs3p9ffff2vRokW6ePGiqlSpop49e2ZpblrA3WifQP6SkJCgN998U5MmTVJ0dLRCQ0PVqFEjBQcHa8eOHTp79qzuuusuffDBB6pevXqGdVksFi1atEhTpkzR4sWL5evrq3vuuUcvv/yyatWqla04H3jgAX377bdauHChevTokWn5Dz74QC+99JL8/PzUunVrXbp0SceOHdPUqVPVr1+/bMUC5KVTp05pw4YNOn36tBISEhQSEqLKlSurRYsWWeo3o6KitGbNGh0+fFgJCQm65ZZb1LBhQzVr1szpOdVT0W/C01y9elWrVq3SmTNndPnyZQUGBiosLEx169bV7bffbveD2q6Ki4vT2rVrdeDAAV29elW33HKLKlSooA4dOlh/G8WVWGmf8BS53TZzEm0zf3A2v0tiPYeRWAcAAIV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      "text/plain": [
       "<Figure size 1400x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sets = list()\n",
    "percents = list()\n",
    "\n",
    "for df in all_stopping:\n",
    "    by_arch = df.groupby('arch')\n",
    "    where_converged = by_arch.apply(get_epoch_converged).reset_index()\n",
    "    only_converged_arches = pd.DataFrame(where_converged.loc[where_converged.epoch_converged!=np.inf,:])\n",
    "    sets.append(only_converged_arches.epoch_converged.to_list())    \n",
    "\n",
    "    percent_converged = len(where_converged[where_converged.epoch_converged!=np.inf].index) / len(where_converged.index) * 100\n",
    "    percents.append(percent_converged)\n",
    "    print(\"percent converged is:\", percent_converged)\n",
    "\n",
    "data_to_plot = sets\n",
    "\n",
    "fig, ax = plt.subplots(layout='constrained', figsize=(14,8))\n",
    "colors = cm.viridis(np.linspace(0.2, 0.95, 6))\n",
    "\n",
    "ax = fig.add_axes([0,0,1,1])\n",
    "\n",
    "ax.set_ylim(0, 25)\n",
    "ax.set_xticklabels(['', '1 GPU', '4 GPUs', '1 GPU', '4 GPUs', '1 GPU', '4 GPUs'], font=tick_font)\n",
    "ax.set_yticklabels([str(int(i))for i in ax.get_yticks()], font=tick_font)\n",
    "ax.set_ylabel('Number of Epochs', font=lfont)\n",
    "\n",
    "\n",
    "\n",
    "bp = ax.violinplot(data_to_plot, showmeans=True)\n",
    "colors=[\"#7B7BFF\", \"#3231A0\", \"#6ED7BA\", \"#209474\", \"#ffa257\", \"xkcd:orange\"]\n",
    "\n",
    "bp['cmeans'].set_color('black')\n",
    "bp['cmeans'].set_linewidth(4)\n",
    "\n",
    "for pc, color, percent in zip(bp['bodies'], colors, percents):\n",
    "    pc.set_facecolor(color)\n",
    "    pc.set_edgecolor('black')\n",
    "    pc.set_linewidth(1.25)\n",
    "    pc.set_label(str(int(percent))+'%')\n",
    "    pc.set_alpha(1)\n",
    "\n",
    "bp['bodies'][0].set_edgecolor('black')\n",
    "\n",
    "lower = [\"Low Beam\", \"Medium Beam\", \"High Beam\"]\n",
    "for i, p in enumerate(percents):\n",
    "    ax.text(x=i + 0.9, y=3, s=str(int(p))+'%', font=legend_font)\n",
    "\n",
    "ax.text(x=1.2, y=-2, s=lower[0], font=lfont)\n",
    "ax.text(x=3.1, y=-2, s=lower[1], font=lfont)\n",
    "ax.text(x=5.25, y=-2, s=lower[2], font=lfont)\n",
    "\n",
    "plt.savefig('figures/figure7.png', bbox_inches='tight')\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Figure 8 - Time Savings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def get_run_time(row):\n",
    "    days = int(row.split('-')[0])\n",
    "    hours = int(row.split('-')[1].split('_')[0])\n",
    "    minutes = int(row.split('-')[1].split('_')[1])\n",
    "    seconds = int(row.split('-')[1].split('_')[2])\n",
    "    time = timedelta(days=days, hours=hours, minutes=minutes, seconds=seconds)\n",
    "    return time\n",
    "\n",
    "def get_run_seconds(row):\n",
    "    days = int(row.split('-')[0])\n",
    "    hours = int(row.split('-')[1].split('_')[0])\n",
    "    minutes = int(row.split('-')[1].split('_')[1])\n",
    "    seconds = int(row.split('-')[1].split('_')[2])\n",
    "    time = timedelta(days=days, hours=hours, minutes=minutes, seconds=seconds)\n",
    "    return time.total_seconds()\n",
    "\n",
    "def plot_times():\n",
    "    time_df = pd.read_csv('./icpp_training_results/time_to_run.csv')\n",
    "\n",
    "    # DataFrame filtering conditions\n",
    "    b14, b15, b16 = (time_df['dataset']==14), (time_df['dataset']==15), (time_df['dataset']==16)\n",
    "    no_stop, stop = (time_df['stopping']==False), (time_df['stopping']==True)\n",
    "    gpu1, gpu4 = (time_df['gpu']==1), (time_df['gpu']==4)\n",
    "    time_format = 'total_seconds'\n",
    "\n",
    "    # Filtering data\n",
    "    no_stop_1e14 = np.array([time_df[b14 & no_stop & gpu1][time_format].item(), time_df[b14 & no_stop & gpu4][time_format].item()])/secs\n",
    "    no_stop_1e15 = np.array([time_df[b15 & no_stop & gpu1][time_format].item(), time_df[b15 & no_stop & gpu4][time_format].item()])/secs\n",
    "    no_stop_1e16 = np.array([time_df[b16 & no_stop & gpu1][time_format].item(), time_df[b16 & no_stop & gpu4][time_format].item()])/secs\n",
    "\n",
    "    stop_1e14 = np.array([time_df[b14 & stop & gpu1][time_format].item(), time_df[b14 & stop & gpu4][time_format].item()])/secs\n",
    "    stop_1e15 = np.array([time_df[b15 & stop & gpu1][time_format].item(), time_df[b15 & stop & gpu4][time_format].item()])/secs\n",
    "    stop_1e16 = np.array([time_df[b16 & stop & gpu1][time_format].item(), time_df[b16 & stop & gpu4][time_format].item()])/secs\n",
    "\n",
    "    epochs_run = {\n",
    "        'NSGA-Net': (no_stop_1e14[0], no_stop_1e15[0], no_stop_1e16[0]),\n",
    "        'A4NN (1 GPU)': (stop_1e14[0], stop_1e15[0], stop_1e16[0]),\n",
    "        'A4NN (4 GPUs)': (stop_1e14[1], stop_1e15[1], stop_1e16[1]),\n",
    "    }\n",
    "\n",
    "    x = np.arange(len(beams))  # the label locations\n",
    "    width = 0.19  # the width of the bars\n",
    "    multiplier = 0\n",
    "\n",
    "    fig, ax = plt.subplots(layout='constrained', figsize=(14,10))\n",
    "    colors = [\"xkcd:grey\", \"xkcd:orange\", \"xkcd:blue\"]\n",
    "\n",
    "    for index, (label, times) in enumerate(epochs_run.items()):\n",
    "        offset = width * multiplier\n",
    "        rects = ax.bar(x + offset, times, width, label=label, color=colors[index]) \n",
    "        labels = [round(time, 2) for time in times]\n",
    "        ax.bar_label(rects, labels=labels ,padding=2, font=bar_font)\n",
    "        multiplier += 1\n",
    "\n",
    "    # Labels, title, x-axis tick labels, etc.\n",
    "    ax.set_ylabel('Run Time (hours)', font=lfont)\n",
    "    ax.xaxis.label.set_color('black')\n",
    "    ax.set_xlabel('Beam Intensity', font=lfont)\n",
    "    ax.yaxis.label.set_color('black')\n",
    "\n",
    "    ax.set_xticks(x + width, beams)\n",
    "    ax.set_xticklabels(beams, color='black', font=tick_font)\n",
    "    ax.set_yticklabels(ax.get_yticks(), color='black', font=tick_font)\n",
    "\n",
    "    ax.legend(loc=\"upper center\", bbox_to_anchor=(0.5, -0.1),  ncol=4, prop=legend_font, frameon=False)\n",
    "    display(fig)\n",
    "    plt.savefig('figures/figure8.png')\n",
    "    plt.close()\n",
    "    \n",
    "    return\n",
    "\n",
    "def save_and_plot_times():\n",
    "    gpu=[1,1,1,1,1,1,4,4,4,4,4,4]\n",
    "    stopping=[False, False, False, True, True, True, False, False, False, True, True, True]\n",
    "    dataset=['14','15','16','14','15','16','14','15','16','14','15','16']\n",
    "    time=['2-02_01_42','2-03_52_23','2-00_38_20','1-22_33_04','1-12_05_38','1-08_18_16','0-14_32_18','0-14_54_32','0-13_53_12','0-12_03_46','0-09_10_05','0-09_27_38']\n",
    "\n",
    "    time_df = pd.DataFrame()\n",
    "    time_df['gpu'] = gpu\n",
    "    time_df['dataset'] = dataset\n",
    "    time_df['stopping'] = stopping\n",
    "    time_df['time'] = time\n",
    "    time_df['total_time'] = time_df['time'].apply(get_run_time)\n",
    "    time_df['total_seconds'] = time_df['time'].apply(get_run_seconds)\n",
    "\n",
    "    time_df.to_csv('./icpp_training_results/time_to_run.csv', index=False)\n",
    "    plot_times()\n",
    "    return \n",
    "\n",
    "save_and_plot_times()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.9.12 ('base')",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.16"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "5d8e2faa28c815775b3c5206064f2fafd40aba95554cafadafdc63449a987d0c"
   }
  }
 },
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